Spaces:
Runtime error
Runtime error
update gradio
Browse files
app.py
CHANGED
@@ -25,8 +25,6 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
|
|
25 |
# Download official weights
|
26 |
if not os.path.exists("saved_models"):
|
27 |
os.mkdir("saved_models")
|
28 |
-
# MODEL_PATH_URL = "https://drive.google.com/uc?id=1KyMpRjewZdyYfxHPYcd-ZbanIXtin0Sn"
|
29 |
-
# gdown.download(MODEL_PATH_URL, "saved_models/isnet.pth", use_cookies=False)
|
30 |
os.system("mv isnet.pth saved_models/")
|
31 |
|
32 |
class GOSNormalize(object):
|
@@ -123,13 +121,13 @@ hypar["model"] = ISNetDIS()
|
|
123 |
net = build_model(hypar, device)
|
124 |
|
125 |
|
126 |
-
def inference(image
|
127 |
image_path = image
|
128 |
|
129 |
image_tensor, orig_size = load_image(image_path, hypar)
|
130 |
mask = predict(net, image_tensor, orig_size, hypar, device)
|
131 |
|
132 |
-
pil_mask = Image.fromarray(mask).convert(
|
133 |
im_rgb = Image.open(image).convert("RGB")
|
134 |
|
135 |
im_rgba = im_rgb.copy()
|
@@ -140,7 +138,7 @@ def inference(image: Image):
|
|
140 |
|
141 |
title = "Highly Accurate Dichotomous Image Segmentation"
|
142 |
description = "This is an unofficial demo for DIS, a model that can remove the background from a given image. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below.<br>GitHub: https://github.com/xuebinqin/DIS<br>Telegram bot: https://t.me/restoration_photo_bot<br>[![](https://img.shields.io/twitter/follow/DoEvent?label=@DoEvent&style=social)](https://twitter.com/DoEvent)"
|
143 |
-
article = "<div><center><img src='https://visitor-badge.glitch.me/badge?page_id=
|
144 |
|
145 |
interface = gr.Interface(
|
146 |
fn=inference,
|
@@ -151,6 +149,5 @@ interface = gr.Interface(
|
|
151 |
description=description,
|
152 |
article=article,
|
153 |
allow_flagging='never',
|
154 |
-
theme="default",
|
155 |
cache_examples=False,
|
156 |
-
).launch(
|
|
|
25 |
# Download official weights
|
26 |
if not os.path.exists("saved_models"):
|
27 |
os.mkdir("saved_models")
|
|
|
|
|
28 |
os.system("mv isnet.pth saved_models/")
|
29 |
|
30 |
class GOSNormalize(object):
|
|
|
121 |
net = build_model(hypar, device)
|
122 |
|
123 |
|
124 |
+
def inference(image):
|
125 |
image_path = image
|
126 |
|
127 |
image_tensor, orig_size = load_image(image_path, hypar)
|
128 |
mask = predict(net, image_tensor, orig_size, hypar, device)
|
129 |
|
130 |
+
pil_mask = Image.fromarray(mask).convert('L')
|
131 |
im_rgb = Image.open(image).convert("RGB")
|
132 |
|
133 |
im_rgba = im_rgb.copy()
|
|
|
138 |
|
139 |
title = "Highly Accurate Dichotomous Image Segmentation"
|
140 |
description = "This is an unofficial demo for DIS, a model that can remove the background from a given image. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below.<br>GitHub: https://github.com/xuebinqin/DIS<br>Telegram bot: https://t.me/restoration_photo_bot<br>[![](https://img.shields.io/twitter/follow/DoEvent?label=@DoEvent&style=social)](https://twitter.com/DoEvent)"
|
141 |
+
article = "<div><center><img src='https://visitor-badge.glitch.me/badge?page_id=max_skobeev_dis_cmp_public' alt='visitor badge'></center></div>"
|
142 |
|
143 |
interface = gr.Interface(
|
144 |
fn=inference,
|
|
|
149 |
description=description,
|
150 |
article=article,
|
151 |
allow_flagging='never',
|
|
|
152 |
cache_examples=False,
|
153 |
+
).queue(concurrency_count=1, api_open=True).launch(show_api=True, show_error=True)
|